Winter2016
FW 544: Quantitative Decision Analysis for Fish and Wildlife Management, Winter 2015
Instructor: Jim Peterson, Office: 176 Nash Hall, ph: 737-1963
office hours: please contact Jim
email: jt.peterson@oregonstate.edu
http://people.oregonstate.edu/~peterjam/
Meeting Periods
Lecture: Wed-Fri 2:00- 3:20 pm, Nash 033
Computer Lab: Monday 2:00-4:50, Withycombe Hall 205
Welcome to Winter 2015! All course materials will be available on this website with the exception of the readings from Conroy and Peterson (2013) that are available as an e-book through the OSU library or you could choose to purchase your own copy.
Winter 2015 Syllabus
-->>Please be sure to download all files prior to attending class.
Schedule (subject to modification)
Date
5-Jan
7-Jan
9-Jan
12-Jan
14-Jan
16-Jan
19-Jan
21-Jan
23-Jan
26-Jan
28-Jan
30-Jan
2-Feb
4-Feb
6-Feb
9-Feb
11-Feb
13-Feb
16-Feb
18-Feb
20-Feb
23-Feb
25-Feb
27-Feb
2-Mar
4-Mar
6-Mar
9-Mar
11-Mar
13-Mar
Topic
Readings1
Assignment2
Structuring your personal objectives*
Information theoretic modeling exercise
Cross-validation modeling exercise
Create and parametrize an influence diagram
*Expert elicitation of fellow students
Hierarchical modeling exercise*
Create a decision model and solve via simulation
Introduction to computing in R;
Lab notes, R scripts, etc.
Introduction to decision making and natural resource management;
Lecture notes
Uncertainty and decision making;
Lecture notes
C&P, Chapters 1, 3
C&P, Chapter 5, pp. 80-100; Chapter 7, pp. 193-197
Probability and simple simulation;
Lab notes, R scripts, etc.
Identifying and structuring objectives;
Lecture notes
Utilities: functions, constraints, and marginal gain;
Lecture notes
C & P, Chapter 3, pp. 24-37
C & P, Chapter 3, pp. 38- 55
Martin Luther King, Jr. Day observed: No Classes
Role of ecological modeling and multiple working hypotheses;
Lecture notes
Review of generalized linear modeling;
Lecture notes
C&P, Chapter 5, pp. 100-116
Statistical uncertainty and model accuracy; Lecture notes
Bayesian probability and concepts;
Lecture notes
C&P, Chapter 5, pp. 140-146
C&P, Chapter 5, p. 129-137
Cross-validation and expected error rate estimation;
Lab notes, R scripts, etc.
Influence diagrams (ID), Directed Acyclic Graphs: construction and parametrization; Lecture notes
Hierarchical models;
Lecture notes
C&P, Chapter 6, pp.147- 179
C&P, Chapter 5, pp. 116- 129
Constructing and parameterizing graphical models;
Hands-on free for all but be sure to download the newest version of Netica and save to your network space prior to completing the lab.
Combining information across studies: meta-analysis;
Lecture notes
Expert elicitation; short lab (do on your own)
Lecture notes
C&P, Chapter 6, pp. 179-191
Hierarchical modeling and meta-analysis;
Lab notes, R scripts, etc.
Decision modeling and population dynamics;
Lecture notes
Ecological simulation of multiple popns: meta-population modeling;
Lecture notes
Transition probability matrix examples
Simulation modeling in R;
Lab notes, R scripts, etc.
Sensitivity analysis
Lecture notes
Sequential dynamic decision making: reducing uncertainty through Adaptive Resource Management (ARM);
Lecture notes
Sensitivity analysis;
Lab notes, R scripts, etc.
Optimization: Identifying the best decision; Lecture notes
Working with stakeholders and governance
Lecture Notes
Optim
C&P, Chapter 7, pp. 203-220
C&P, Chapter 7, pp. 220-230
C&P, Chapter 8
C&P, Chapter 4
C&P, Chapter 7, pp. 197-203
ization in R; Lab notes, R scripts, etc.Tribble trivia
Risk and advanced topics;
Lecture notes
Presentations of projects
1Students are required to read material before lecture.
2Assignments with asterisks indicates that methods and results format is NOT REQUIRED
Examples
Methods and results for generalized linear modeling exercise
Probabilistic network model write-up
Decision model write-up
Project final report
Project presentation
Additional Resources
Companion to Conroy and Peterson: Decision making in natural resource management: a structured, adaptive approach
A little R help: OSU Fisheries and Wildlife R course
Software for course